Discover Artificial Intelligence

Abstract One-stream transformer trackers have received widespread attention for their excellent discriminatory ability. However, most of the existing trackers try to mine more information about the target while ignoring the exploitation of the background around it. In this work We propose a single-stream progressive background elimination transformer for target tracking. This model employs a prog…

The growing integration of renewable energy into modern grids demands accurate wind power forecasting to ensure stable operations and efficient energy management. Existing methods often overlook nonlinear patterns and fail to fully exploit the Internet of Things (IoT)-based data acquisition, along with advanced deep learning-driven optimization for grid-connected power prediction and optimization…

In the context of the digital era’s unprecedented expansion, the proliferation of disinformation and fabricated narratives has emerged as a critical societal challenge. This trend not only weakens the trust in mainstream media but also exposes internet users to substantial risks, as they often unknowingly propagate misleading content. The emergence of diverse media formats, including textual fabr…

With high-stakes industries such as healthcare, finance, and autonomous systems, an increasing number of cognitive artificial intelligence are being utilized, which presents new challenges for developing calibrated trust. The complexity of trust involves balancing reliance and skepticism. Mistrust and misalignment cause complacency towards automation, premature skepticism, and outright rejection …

Abstract The rapid development of artificial intelligence (AI) and deep learning has driven innovation across multiple fields. This study aims to provide a comprehensive overview of deep learning research within AI from 2019 to 2025. A total of 1214 relevant articles from the Web of Science were systematically analyzed using bibliometric, network, and content analysis methods. VOSviewer and R Stu…

Abstract Corporate bankruptcy prediction is a high-stakes artificial intelligence (AI) task characterized by extreme class imbalance and asymmetric misclassification costs. Although ensemble learning models have shown strong predictive performance, most existing studies rely on cost-insensitive metrics and fixed decision thresholds, which can misrepresent real-world decision utility. This study r…

Breweries, as part of the food manufacturing sector, face increasing demands to reconcile traditional craftsmanship with modern expectations for sustainability, efficiency, and consistent product quality. Recent advances in digitalization and machine learning (ML) offer new opportunities to monitor, predict, and optimize complex production processes such as brewing. For micro-breweries, however, …